Big Data In Women's Healthcare

Is data analysis finally going to give women the equity they have long strived for in healthcare?


The plight of men and women when it comes to healthcare has never been on equal footing. This fundamentally comes down to the fact that women get pregnant, an inherently dangerous process, and men do not. However, for most of human history, there was no real healthcare for either gender - the best anyone had to offer were educated guesses, superstitions or ludicrous conjecture.

Yet, while a lot has changed through the centuries since, I don't think anyone can reasonably disagree with the idea that men and women still don't have an equal expectation of care today. A regular stat produced to illustrate the sheer absurdity of the situation is that PMS symptoms, which affect 90% of women to some degree, has 5 times fewer studies than erectile dysfunction, an issue which only affects 20% of men.

We didn't just find ourselves here all of a sudden, the west has long been geared towards the disregard of female pain/problems. The advent of the scientific method didn't change this mentality, it just muddied it. If you need more proof of how far removed the medical realities of women have been from men who treated them, you but need to research how the vibrator became the 5th home appliance to be electrified.

However, a new development seems finally to be turning the tide - data analysis. Yet, for a myriad of reasons, this isn't being done. This is because, even with all the data in the world, a choice still has to be made to look at it, something experts like Anna Villarreal say just isn't happening enough.

"The scariest element is that really good companies are not being funded because of female leadership versus male," says Villarreal, founder and CEO of LifeStory Health. "I see a lot of women-led and/or women-founded healthcare companies struggle to get the same amount of funding as their male counterpart. Between 2011 and 2013, companies with a female CEO received $1.5 billion in venture capital investment while companies led by men received 34 times that amount. Yet, research indicates that women tend to be more successful when they lead ventures. A recent study of 22,000 publicly traded companies found that an increase in leadership positions in a company for women from 0% to 30% is associated with an increase of 15% in profitability. Female tech entrepreneurs, on average, generate a 35% higher return on investment than their male counterparts."

Anna's company, LifeStory, is a bio-science company focused on the female biology. She is also one of the speakers at this year's Big Data Analytics summit and has a deep understanding of the many challenges women face daily. Whether these are due to unconscious or conscious biases, they all have real-world consequences which, we as a society, simply don't have any excuse for anymore. "If data was being used effectively," Villarreal explains, "there would be significantly more funded women-led or founded companies and women’s healthcare would be in a much better place."

However, according to Villarreal, we are a long way from this seeming utopia. For example, there are issues critically important to women which many aren't even aware of, such as sex-specific testing. "The second worrisome element to data not being utilized effectively is regarding sex-specific testing. The first-ever scientific statement about women and heart disease highlights other disparities between sexes. Within the year of a first heart attack, survival rates are lower in women than in men. Within five years, 47% of the women will die, develop heart failure, or suffer from a stroke, compared with just 36% of the men."

While most of us now view the idea of Silicon Valley as the home of progressive action with an ample dose of disillusionment, companies like Villarreal's have a chance of making a difference. This is because they are centering their message on the data and the insights they have uncovered from it. The use of data helps reframe an argument which has traditionally been seen as moralistic, as one which just makes good business sense. VC's have been conditioned to respond to data-driven insights, so even if they aren't actively looking for ways to help women, it doesn't mean they are able to ignore the facts when they are presented.

This is why, for example, using visualizations to convey facts is incredibly effective. It doesn't rely on anything but your eyes and ability to reason to convey complicated facts. This allows it to create a shortcut around peoples prejudices. "I find visualization useful when showing the presence versus absence or difference in concentration levels of protein biomarkers in the blood." Villarreal explains, "The difference can be quite staggering and it always looks more powerful when displayed visually. I also think that when presented visually it is very easy to see the disparity in women funded companies versus male as well as males and females represented in clinical studies. However, with a statistic such as this, it should not matter how it is communicated. In a review of over 600 basic and translational science studies, reviewers found that 80% of the studies used only males."

The general public has long held the idea that data-driven decisions are cold and inhuman. However, if they paint a more honest picture of the world, it makes them inherently more inclusive, at least relative to what we have now. Data-driven decision making is the closest to bias-free humans are capable of. And with the integration of machine learning becoming more prevalent, peoples prejudices are having less access to the steering wheel. We can only hope that one day it helps us achieve a more equitable world.

"Over the next five years," Villarreal concludes, "I foresee machine learning continuing to change the way people use data. Our strategy to prepare ourselves has already begun. In conjunction with Northeastern University in Boston, as well their campus in San Francisco, we have created a two-year roadmap to lay-out three things: 1) a HIPAA compliant data warehouse; 2) a data marketplace and; 3) consumer access to their own data."

"SimplyVital Health has partnered with us to use their unique key pair system blockchain technology, and machine learning to establish a data marketplace. Our cohort of patients is extremely valuable, especially to researchers, and the possibility of sharing data to accelerate women’s healthcare is promising."

For similar insights into how companies are improving patient outcomes with data analytics, attend our Big Data & Analytics in Healthcare Summit happening in Philadelphia, May 22-23.


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